Ozasa Kazunari, Aono Masashi, Maeda Mizuo, Hara Masahiko
Advanced Science Institute, RIKEN, Wako, Saitama, Japan.
Biosystems. 2010 May;100(2):101-7. doi: 10.1016/j.biosystems.2010.02.002. Epub 2010 Feb 10.
To explore possible forms of unconventional computers that have high capacities for adaptation and exploration, we propose a new approach to developing a biocomputer based on the photophobic reactions of microbes (Euglena gracilis), and perform the Monte-Carlo simulation of Euglena-based neural network computing, involving virtual optical feedback to the Euglena cells. The photophobic reactions of Euglena are obtained experimentally, and incorporated in the simulation, together with a feedback algorithm with a modified Hopfield-Tank model for solving a 4-city traveling salesman problem. The simulation shows high performances in terms of (1) reaching one of the best solutions of the problem, and (2) searching for a number of solutions via dynamic transition among the solutions. This dynamic transition is attributed to the fluctuation of state variables, global oscillation through feedback instability, and the one-by-one change of state variables.
为了探索具有高适应和探索能力的非传统计算机的可能形式，我们提出了一种基于微生物（纤细裸藻）的避光反应开发生物计算机的新方法，并对基于裸藻的神经网络计算进行了蒙特卡罗模拟，其中涉及对裸藻细胞的虚拟光反馈。通过实验获得了裸藻的避光反应，并将其与用于解决4城市旅行商问题的具有改进霍普菲尔德-坦克模型的反馈算法一起纳入模拟。模拟结果在以下方面表现出高性能：（1）找到该问题的最佳解决方案之一；（2）通过解决方案之间的动态转换搜索多个解决方案。这种动态转换归因于状态变量的波动、反馈不稳定性导致的全局振荡以及状态变量的逐个变化。
